import os
import sys

# Add current directory to path so we can import app
sys.path.append(r"f:\BRATS\Interface")
from app import get_available_models, run_inference

def main():
    image_path = r"f:\BRATS\Interface\Image\BraTS20_Training_001_flair_slice77.png"
    result_dir = r"f:\BRATS\Interface\static\results"
    
    if not os.path.exists(result_dir):
        os.makedirs(result_dir)

    models = get_available_models()
    results = []

    print(f"Found models: {models}")
    print(f"Testing with image: {image_path}")
    print("-" * 40)

    for model in models:
        result_path = os.path.join(result_dir, f"test_result_{model}.png")
        print(f"Testing model: {model}...")
        try:
            detected, confidence = run_inference(image_path, result_path, model)
            results.append({
                "model": model,
                "detected": detected,
                "confidence": confidence,
                "result_path": result_path
            })
            print(f" -> Detected: {detected}, Confidence: {confidence:.2f}%")
        except Exception as e:
            print(f" -> Error with model {model}: {e}")

    # Rank the models based on confidence
    results.sort(key=lambda x: x["confidence"], reverse=True)

    print("\n" + "=" * 60)
    print("  Model Ranking (Best to Worst based on Confidence)")
    print("=" * 60)
    for i, res in enumerate(results, 1):
        print(f"{i}. {res['model']} | Detected: {res['detected']} | Confidence: {res['confidence']:.2f}%")
        
if __name__ == "__main__":
    main()